Markov chain analysis of genetic algorithms in a wide variety of noisy environments

@inproceedings{Nakama2009MarkovCA,
  title={Markov chain analysis of genetic algorithms in a wide variety of noisy environments},
  author={Tak{\'e}hiko Nakama},
  booktitle={GECCO},
  year={2009}
}
We examine the convergence properties of genetic algorithms (GAs) in a wide variety of noisy environments where fitness perturbation can occur in any form for example, fitness functions can be concurrently perturbed by additive and multiplicative noise. We reveal the convergence properties of such GAs by constructing and analyzing a Markov chain that explicitly models the evolution of the algorithms. We compute the one-step transition probabilities of the chain and show that the chain has only… CONTINUE READING